Empirical evaluation demonstrates multimodal kinematic and point-cloud logging in a dual-trailer robotic vehicle, highlighting robust benchmarks for articulated autonomous navigation.
This work presents a comprehensive dataset focusing on a generalised 2-trailer vehicle configuration, utilising a Clearpath Husky A200 as the tractor, pulling two passive trailers. The dataset encompasses a range of measurements, primarily focusing on the pose of the active segment, including its position and attitude. Additionally, it includes crucial data on the joint angles between consecutive segments of the vehicle, specifically the angles between the tractor and the first trailer, as well as between the first and second trailers. Furthermore, the dataset incorporates measurements obtained from a LiDAR sensor installed at the front of the Husky A200. Notably, ground truth position data for the last trailer is provided, accompanied by geographical coordinates in the form of latitude and longitude, facilitating the reconstruction of the local navigation frame.
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Deniz et al. (2024) studied this question.
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